How human vision separately determines object and scene motion. This project aims to enhance understanding of how people process visual scenes containing multiple moving objects of interest. The project intends to measure human visual performance to determine how the brain processes multiple motion signals simultaneously. Expected outcomes include an increased understanding of how we are able to use an evolving visual scene to distinguish between changes due to self-motion and those due to the m ....How human vision separately determines object and scene motion. This project aims to enhance understanding of how people process visual scenes containing multiple moving objects of interest. The project intends to measure human visual performance to determine how the brain processes multiple motion signals simultaneously. Expected outcomes include an increased understanding of how we are able to use an evolving visual scene to distinguish between changes due to self-motion and those due to the motion of multiple moving objects such as crowded city footpaths and busy roads. The results will improve our understanding of failures to see moving objects in challenging viewing conditions (for example, high density traffic), and inform work in the design of autonomous driving and augmented reality display systems.Read moreRead less
Neural plasticity in older adult human vision. This project aims to expand our understanding of age related changes in brain function, specifically plasticity. The project will increase knowledge of the role of an inhibitory neurotransmitter GABA in visual plasticity. Expected outcomes include new knowledge regarding the regulation of brain function in adulthood, enabling future research and planning for societal benefit to older Australia.
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Creating perceptual experts in Australia's policing and security agencies. This project aims to create the next generation of experts in Australia’s policing and national security agencies, by improving crime scene evidence interpretation. Agencies are under pressure to develop more rigorous training practices that go beyond mere intuition and tradition. This project will use a novel approach that directs learning toward the most diagnostic perceptual cues. Expected outcomes include a solid empi ....Creating perceptual experts in Australia's policing and security agencies. This project aims to create the next generation of experts in Australia’s policing and national security agencies, by improving crime scene evidence interpretation. Agencies are under pressure to develop more rigorous training practices that go beyond mere intuition and tradition. This project will use a novel approach that directs learning toward the most diagnostic perceptual cues. Expected outcomes include a solid empirical basis for national training programs designed to create experts that are accurate, reliable, and continuously improving. Improving the training of experts will ensure the integrity of forensics as evidentiary tools available to police, lead to more reliable courtroom convictions and help safeguard Australia from terrorism and crime.Read moreRead less
Listen and learn - statistical learning and the adapting auditory brain. This project aims to explore the link between rapid neural adaptation - a form of learning referred to as statistical learning - and human listening performance in noisy environments. The project aims to generate a new understanding of mechanisms that contribute to listeners' abilities to understand speech in noise, and to complex communication disorders such as dyslexia. Expected outcomes will include increased capacity to ....Listen and learn - statistical learning and the adapting auditory brain. This project aims to explore the link between rapid neural adaptation - a form of learning referred to as statistical learning - and human listening performance in noisy environments. The project aims to generate a new understanding of mechanisms that contribute to listeners' abilities to understand speech in noise, and to complex communication disorders such as dyslexia. Expected outcomes will include increased capacity to investigate a broad range of cognitive and communication functions. Benefits will include potential technologies and algorithms to assist listening (in devices such as hearing aids), language development and reading.Read moreRead less
Robust and Explainable 3D Computer Vision. Computer vision is increasingly relying on deep learning which is fragile, opaque and fails catastrophically without warning. This project aims to address these problems by developing new theory in graph representation of 3D geometric and image data, hierarchical graph simplification and novel modules designed specifically for deep learning over geometric graphs. Using these modules, it aims to design graph convolutional network architectures for self-s ....Robust and Explainable 3D Computer Vision. Computer vision is increasingly relying on deep learning which is fragile, opaque and fails catastrophically without warning. This project aims to address these problems by developing new theory in graph representation of 3D geometric and image data, hierarchical graph simplification and novel modules designed specifically for deep learning over geometric graphs. Using these modules, it aims to design graph convolutional network architectures for self-supervised learning that are robust to failures and provide explainable decisions for object detection and scene segmentation. The outcomes are expected to advance theory in robust deep learning and benefit 3D mapping, surveying, infrastructure monitoring, transport and robotics industries.Read moreRead less
Moving from assumptions to new learning. . Moving from assumptions to new learning. The project aims to investigate the processes that drive new learning
by using automatically evoked brain responses to examine when new information triggers the brain to update
beliefs about the world. The project will generate new knowledge on the maturity of this process at birth, how it
declines with older age and the brain areas critical to the process. The outcomes will provide insight into how
attentio ....Moving from assumptions to new learning. . Moving from assumptions to new learning. The project aims to investigate the processes that drive new learning
by using automatically evoked brain responses to examine when new information triggers the brain to update
beliefs about the world. The project will generate new knowledge on the maturity of this process at birth, how it
declines with older age and the brain areas critical to the process. The outcomes will provide insight into how
attentional resources are automatically marshalled when beliefs are challenged, and it will help identify the consequences for learning when a system is immature, or the process breaks down with increasing age.Read moreRead less
Reading facial expressions from real and virtual humans. This project aims to advance understanding of human emotional communication and improve human rapport with the virtual humans and avatars that are rapidly infiltrating our social world. Using two unique stimulus sets - naturalistic human expressions and highly realistic virtual faces - together with powerful genetic, experimental, and individual differences designs, the project expects to answer previously intractable questions in emotion ....Reading facial expressions from real and virtual humans. This project aims to advance understanding of human emotional communication and improve human rapport with the virtual humans and avatars that are rapidly infiltrating our social world. Using two unique stimulus sets - naturalistic human expressions and highly realistic virtual faces - together with powerful genetic, experimental, and individual differences designs, the project expects to answer previously intractable questions in emotion science, as well as deliver tangible outcomes, such as new psychological tests to better understand human social connection. This should provide significant benefits, by improving emotion communication and offering a new perspective on how artificial intelligence can best serve human social needs.
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How brain oscillations influence our behaviour. This project aims to reveal how sudden, intense stimuli impair or facilitate concurrent actions. Startling sounds can disrupt the execution of movements and distract attention from vital events in the environment, with potential disastrous consequences when handling complex equipment such as airplanes, cars and trucks, or surgical instruments. This project will combine classic experimental and novel neuro-modulatory techniques with the measurement ....How brain oscillations influence our behaviour. This project aims to reveal how sudden, intense stimuli impair or facilitate concurrent actions. Startling sounds can disrupt the execution of movements and distract attention from vital events in the environment, with potential disastrous consequences when handling complex equipment such as airplanes, cars and trucks, or surgical instruments. This project will combine classic experimental and novel neuro-modulatory techniques with the measurement of oscillatory brain activity. Expect outcomes will inform theories of cognitive function and the design of interventions to reduce the negative effects of sudden, distracting events.Read moreRead less
Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less